Evidence map›Paper›PMID 41743242›Full record

ArticleIranian journal of medical sciences2026

Exploring Potential Drug-Drug Interactions: A Cross-Sectional Study of 1 Million e-Prescriptions Across Medical Specialties in Shiraz, Iran (2021-2024).

Pedram Porbaha, Mohammad Hasannejad, Negar Ahvar, Mojtaba Shafiekhani, Nahid Abolpour, Mehrdad Sharifi

Abstract read
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Article in Iranian journal of medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Pedram PorbahaDepartment of Pharmaceutics, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad HasannejadStudent Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
Negar AhvarStudent Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
Mojtaba ShafiekhaniDepartment of Clinical Pharmacy, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Nahid AbolpourDepartment of Artificial Intelligence in Medical Sciences, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Mehrdad SharifiDepartment of Emergency Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Drug-drug interactions (DDIs) are among the most important medical errors that can lead to adverse effects, increased toxicity, or reduced treatment efficacy. The frequency and severity of DDIs vary across specialties. However, studies covering multiple specialties in Iran are few and not up-to-date. This study aims to fill this gap by offering a large-scale, multi-specialty analysis of DDIs in Iran using real-world e-prescription data. Methods: This study analyzed pharmacological DDIs in 1,049,769 e-prescription records from Shiraz, Iran, spanning from November 2021 to February 2024. We used Lexicomp Results: The analysis revealed that 38.77% of prescriptions contained at least one C, D, or X DDI. Dexamethasone, ketorolac, quetiapine, and aspirin were the drugs most commonly involved. The most frequent DDIs occurred between aprepitant and dexamethasone, ketorolac, and naproxen, aprepitant and doxorubicin, prednisolone, and tacrolimus, and diclofenac sodium and ketorolac. The medical specialties with the highest incidence of D or X level DDIs were rheumatology, endocrinology, orthopedics, oncology, internal medicine, emergency services, and psychiatry. The average counts of D or X DDIs per prescription were 0.53, 0.41, 0.40, 0.40, 0.26, 0.24, and 0.23, respectively. Conclusion: This study underscores the need for provider vigilance and proactive measures, such as training and e-prescription alerts, to ensure patient safety.

Indexed as

Cross-sectional studiesDrug interactionsElectronic prescribingIranPrevalence

Identifiers

PMID41743242
PMCPMC12929907

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.